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Step-by-step guide: Generative AI for your business

IBM Journey to AI blog

AI Developer / Software engineers: Provide user-interface, front-end application and scalability support. Organizations in which AI developers or software engineers are involved in the stage of developing AI use cases are much more likely to reach mature levels of AI implementation.

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Dr. Pandurang Kamat, Chief Technology Officer, Persistent Systems – Interview Series

Unite.AI

As an AI-powered Digital Engineering enterprise, Persistent has embraced GenAI to revolutionize various aspects of the software engineering lifecycle. Legacy systems often lack comprehensive documentation, hindering the ability of AI to grasp their interdependencies effectively.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Data quality control: Robust dataset labeling and annotation tools incorporate quality control mechanisms such as inter-annotator agreement analysis, review workflows, and data validation checks to ensure the accuracy and reliability of annotations. Data monitoring tools help monitor the quality of the data.

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12 AI Insight Talks to Help Improve Your Company’s AI Game at ODSC West

ODSC - Open Data Science

By leveraging Delphina, teams can significantly reduce the manual work required to set prices, optimize supply chains, prevent fraud, or personalize products, all while keeping data scientists in the driver’s seat, ensuring efficiency without sacrificing control.

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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning Blog

It includes processes for monitoring model performance, managing risks, ensuring data quality, and maintaining transparency and accountability throughout the model’s lifecycle. He is focused on AI/ML technology, ML model management, ML governance, and MLOps to improve overall organizational efficiency and productivity.

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11 Trending LLM Topics Coming to ODSC West 2024

ODSC - Open Data Science

This talk will also cover the implementation of the RAISE framework, which stands for Responsible AI Security Engineering, designed to provide a step-by-step approach to building secure and resilient AI systems.

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A Comprehensive Guide on Deep Learning Engineers

Pickl AI

Collaboratio n: Working with data scientists, software engineers, and other stakeholders to integrate Deep Learning solutions into existing systems. Data Quality and Quantity Deep Learning models require large amounts of high-quality, labelled training data to learn effectively.